Notes on codes, projects and everything
While the previous file structure works well, I decided to tune some details before deploying the latest WordPress release. Besides that, I also started a new theme development project after my last theme which was developed more than 2 years ago. Thankfully, everything seems to work so far.
Semantic Web is not just about putting data on the web, but also making links to allow a person as well as a machine to explore the web of data. Links are made in the web of data connects arbitrary things together as described by RDF as opposed to links in the web of hypertext, where links connects to only web-resources. Linkage of arbitrary things then allow related things to be found while performing search.
As the name implies, Resource Definition Framework, or RDF in short, is a language to represent information about resources in world wide web. Information that can be represented is mostly metadata like title (assuming the resource is a web-page), author, last modified date etc. Besides representing resource that is network-accessible, it can be used to represent things that cannot be accessed through the network, as long as it can be identified using a URI.
I am currently preparing myself in applying a postgrad programme and is looking for a research topic. At first I wanted to do something that is related to cloud computing but after some discussion with people around me, they suggest me to do something on semantic web. While posting my notes here, I realized that I had posted something on semantic network that looks like the base of semantic web here (Post still “Under construction” as of writing, will post the diagrams later tonight).
I often struggle to get my Javascript code organized, and have tried numerous ways to do so. I have tried putting relevant code into classes and instantiate as needed, then abuse jQuery’s data()
method to store everything (from scalar values to functions and callbacks). Recently, after knowing (briefly) how a jQuery plugin should be written, it does greatly simplify my code.
array_map function is a function that I use the most in my php scripts recently. However, there are times where I want to pass some non-array into it, therefore often times I have code like the snippet shown below:
$result = array_map(
'some_callback',
array_fill(0, count($some_array), 'some_string'),
array_fill(0, count($some_array), 'some_other_string'),
$some_array
)
It doesn’t look good IMO, as it makes the code looks complicated. Hence, after seeing how the code may vary in all different scenarios, I created some functions to clean up the array_map call as seen above. Code snippet after the jump
Just happened to see this post a few months ago, and the author created another cloud that uses almost the same technique to ‘visualize’ a list of countries. The author uses PHP to generate the cloud originally and I thought I may be able to do in javascript. After some quick coding I managed to produce something similar to the first example, source code after the jump.
After delaying for quite some time, I think I should start the project before I get bored with it. The project will be either hosted on this current domain (coolsilon.com) at least for now and will probably move to another domain if needed. The site will be either a blog aggregator or just a simple article submission site that works kinda like digg / reddit, however, to be promoted to the frontpage the submission would have to impress the opposite group.
In the previous post, I re-implemented Annoy in 2D with some linear algebra maths. Then I spent some time going through some tutorial on vectors, and expanded the script to handle data in 3D and more. So instead of finding gradient, the perpendicular line in the middle of two points, I construct a plane, and find the distance between it and points to construct the tree.
Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.
This is the second part of the golang learning rant log. Previously on (note (code cslai)) I managed to make each line in the CSV into a hash map. So today I am going to make it into JSON Lines.